Relevant bibliographies by topics / Analysis of Variance (ANOVA)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Analysis of Variance (ANOVA)'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Analysis of Variance (ANOVA)"

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St»hle, Lars, and Svante Wold. "Analysis of variance (ANOVA)." Chemometrics and Intelligent Laboratory Systems 6, no. 4 (1989): 259–72. http://dx.doi.org/10.1016/0169-7439(89)80095-4.

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Thompson, Hilary W., Robertino Mera, and Chandan Prasad. "The Analysis of Variance (ANOVA)." Nutritional Neuroscience 2, no. 1 (1999): 43–55. http://dx.doi.org/10.1080/1028415x.1999.11747262.

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Shahid, Iqbal, Leghari Imdad, Sethar D.V.M. M. Sc Abdullah, Memon Azizullah, and Bhatti M.Ali. "Analysis Of Variance (ANOVA) Cholesterol of Count of Broilers." International Journal of Case Studies 5, no. 7 (2016): 76–79. https://doi.org/10.5281/zenodo.3531378.

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This research investigates that Analysis of variance (ANOVA) Cholesterol ofcount of broilers. It was revealed that reported significant (P>0.05) difference in cholesterol count of broilers among the groups. All-pair-wise (LSD) test indicated that there was significant variation in total protein count between treatment groups B, C, D with control group-A, respectively. The result (Figure-14) indicated that average cholesterol count in groups A, B, C and D was 117.67, 121.67, 118.33 and 124 g/dl, respectively. Maximum cholesterol count of 124 g/dl were noted in group D where the bird fed on H
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Connelly, Lynne M. "Introduction to Analysis of Variance (ANOVA)." MEDSURG Nursing 30, no. 3 (2021): 218. https://doi.org/10.62116/msj.2021.30.3.218.

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Researcher. "BIOLOGICAL DATA INTERPRETATION – ANOVA." International Journal of Biological Sciences (IJBS) 2, no. 1 (2025): 1–7. https://doi.org/10.5281/zenodo.15575762.

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Analysis of Variance (ANOVA) is a pivotal statistical tool used to interpret biological data where comparisons among multiple groups are necessary. This paper discusses the application of ANOVA in biological research, emphasizing its utility in distinguishing differences among treatment groups, species, or experimental conditions. By analyzing variance within and between groups, ANOVA aids in determining the significance of biological effects. The paper further explores the assumptions, methodologies, and interpretation of ANOVA outcomes in the context of biological data. Visual representation
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Maxwell, Scott E., Harold D. Delaney, and Jerry M. Manheimer. "Anova of Residuals and Ancova: Correcting an Illusion by Using Model Comparisons and Graphs." Journal of Educational Statistics 10, no. 3 (1985): 197–209. http://dx.doi.org/10.3102/10769986010003197.

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Analysis of covariance is often conceptualized as an analysis of variance of a single set of residual scores that are obtained by regressing the dependent variable on the covariate. Although this conceptualization of an equivalence between the two procedures may be intuitively appealing, it is mathematically incorrect. If residuals are obtained from the pooled within-groups regression coefficient ( bw), an analysis of variance on the residuals results in an inflated α-level. If the regression coefficient for the total sample combined into one group ( bT) is used, ANOVA on the residuals yields
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Shahid, Iqbal, Leghari Imdad, Sethar D.V.M. M. Sc Abdullah, Memon Azizullah, and Bhatti .M.Ali. "Analysis Of Variance (ANOVA) In Total Protein Count of Broiler." International Journal of Case Studies 5, no. 7 (2016): 80–83. https://doi.org/10.5281/zenodo.3531380.

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This research investigates that Analysis of variance (ANOVA) in total protein count of broiler. Analysis of variance (ANOVA) reported significant (P>0.05) difference in total protein count of broilers among the groups. All-pair-wise (LSD) test indicated that there was significant variation in total protein count between treatment groups B, C, D with control group-A, respectively. The result (Figure-13) indicated that average total protein count in groups A, B, C and D was 3.33, 3.46, 3.53 and 4.03 g/dl, respectively. Maximum total protein count of 4.03 g/dl were noted in group D where the b
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Shelton, Heather K. "BASIC PREMISES OF FACTORIAL ANALYSIS OF VARIANCE (ANOVA)." Experimental Techniques 27, no. 6 (2003): 64–66. http://dx.doi.org/10.1111/j.1747-1567.2003.tb00142.x.

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Milanes-Baños, Norma A. "Step-by-step one-way ANOVA analysis with the Jamovi program." Mexican Journal of Medical Research ICSA 12, no. 23 (2024): 22–26. http://dx.doi.org/10.29057/mjmr.v12i23.10664.

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ANOVA is the acronym for Analysis of Variance, which stands for Analysis of Variance, and is used to establish statistically significant differences between the means of two groups. Currently there are several programs that synthesize this work allowing us to analyse statistical data in a simpler way. In this manuscript we will address a one-way or one-factor analysis of variance, which means that we must have an explanatory variable, also known as an independent variable, which must have two or more categories, we must also have a dependent or response variable of the type quantitatively disc
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Shehu, A., N. S. Dauran, and G. A. Usman. "Analysis of Covariance of Models of Sudoku Squares with no Treatment Effects on Concomitant Variable." Journal of Applied Sciences and Environmental Management 27, no. 11 (2023): 2661–67. http://dx.doi.org/10.4314/jasem.v27i11.39.

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Inclusion of concomitant variable(s) in an analysis of variance (ANOVA) model is an indication that the model is of ANCOVA model provided that there is correlation between the concomitant and response variable. This study employ numerical illustrations of the analysis of covariance of models of Sudoku square with no treatment effects on concomitant variable- Result of the illustration, showed that error variance from the ANCOVA Sudoku square models reduced 12.7761 to 5.5152 for model I; 13.6898 to 6.4690 for model II; 15.7926 to 4.8160 for model III and 16.5152 to 4.9226 for model IV respectiv
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Dissertations / Theses on the topic "Analysis of Variance (ANOVA)"

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Prosser, Robert James. "Robustness of multivariate mixed model ANOVA." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/25511.

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In experimental or quasi-experimental studies in which a repeated measures design is used, it is common to obtain scores on several dependent variables on each measurement occasion. Multivariate mixed model (MMM) analysis of variance (Thomas, 1983) is a recently developed alternative to the MANOVA procedure (Bock, 1975; Timm, 1980) for testing multivariate hypotheses concerning effects of a repeated factor (called occasions in this study) and interaction between repeated and non-repeated factors (termed group-by-occasion interaction here). If a condition derived by Thomas (1983), multivariate
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Halldestam, Markus. "ANOVA - The Effect of Outliers." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-295864.

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This bachelor’s thesis focuses on the effect of outliers on the one-way analysis of variance and examines whether the estimate in ANOVA is robust and whether the actual test itself is robust from influence of extreme outliers. The robustness of the estimates is examined using the breakdown point while the robustness of the test is examined by simulating the hypothesis test under some extreme situations. This study finds evidence that the estimates in ANOVA are sensitive to outliers, i.e. that the procedure is not robust. Samples with a larger portion of extreme outliers have a higher type-I er
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Patrick, Joshua Daniel. "Simulations to analyze Type I error and power in the ANOVA F test and nonparametric alternatives." [Pensacola, Fla.] : University of West Florida, 2009. http://purl.fcla.edu/fcla/etd/WFE0000158.

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Lind, Ingela. "Regressor and Structure Selection : Uses of ANOVA in System Identification." Doctoral thesis, Linköping : Linköpings universitet, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7000.

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An, Qian. "A Monte Carlo study of several alpha-adjustment procedures using a testing multiple hypotheses in factorial anova." Ohio : Ohio University, 2010. http://www.ohiolink.edu/etd/view.cgi?ohiou1269439475.

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Jordaan, Aletta Gertruida. "Empirical Bayes estimation of the extreme value index in an ANOVA setting." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86216.

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Thesis (MComm)-- Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: Extreme value theory (EVT) involves the development of statistical models and techniques in order to describe and model extreme events. In order to make inferences about extreme quantiles, it is necessary to estimate the extreme value index (EVI). Numerous estimators of the EVI exist in the literature. However, these estimators are only applicable in the single sample setting. The aim of this study is to obtain an improved estimator of the EVI that is applicable to an ANOVA setting. An ANOVA setting lends itself naturally to
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Zhang, Bairu. "Functional data analysis in orthogonal designs with applications to gait patterns." Thesis, Queen Mary, University of London, 2018. http://qmro.qmul.ac.uk/xmlui/handle/123456789/44698.

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This thesis presents a contribution to the active research area of functional data analysis (FDA) and is concerned with the analysis of data from complex experimental designs in which the responses are curves. High resolution, closely correlated data sets are encountered in many research fields, but current statistical methodologies often analyse simplistic summary measures and therefore limit the completeness and accuracy of conclusions drawn. Specifically the nature of the curves and experimental design are not taken into account. Mathematically, such curves can be modelled either as sample
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Gonsalez, Camila Gianini [UNESP]. "Metodologias para reconhecimento de padrões em sistemas SHM utilizando a técnica da Impedância Eletromecânica (E/M)." Universidade Estadual Paulista (UNESP), 2012. http://hdl.handle.net/11449/94506.

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Made available in DSpace on 2014-06-11T19:27:13Z (GMT). No. of bitstreams: 0 Previous issue date: 2012-02-24Bitstream added on 2014-06-13T19:14:27Z : No. of bitstreams: 1 gonsalez_cg_me_ilha.pdf: 4679748 bytes, checksum: 5f6a627734b2110f92059053c2470814 (MD5)<br>Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>Pesquisadores de diversas partes do mundo se empenham em desenvolver técnicas capazes de monitorar a integridade de máquinas, veículos e estruturas, principalmente as que a ruptura ou destruiç
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Gonsalez, Camila Gianini. "Metodologias para reconhecimento de padrões em sistemas SHM utilizando a técnica da Impedância Eletromecânica (E/M) /." Ilha Solteira : [s.n.], 2012. http://hdl.handle.net/11449/94506.

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Orientador: Vicente Lopes Junior<br>Banca: Samuel Silva<br>Banca: Michael John Brennan<br>Banca: Carlos Alberto Cimini Junior<br>Resumo: Pesquisadores de diversas partes do mundo se empenham em desenvolver técnicas capazes de monitorar a integridade de máquinas, veículos e estruturas, principalmente as que a ruptura ou destruição possa provocar acidentes e catástrofes. Neste contexto, várias técnicas não destrutivas podem ser utilizadas para monitorar estes sistemas permitindo a realização de reparos e, evitando maiores prejuízos econômicos e danos sociais. A técnica da Impedância Eletromecâni
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Joubert, Ronel. "Factors influencing the degree of burnout experienced by nurses working in neonatal intensive care units." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/20217.

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Thesis (MCur)--Stellenbosch University, 2012.<br>ENGLISH ABSTRACT: Burnout is one of the challenges that nurses are faced with in their stressful and rapidly changing work environment. The vulnerability of nurses to burnout remains a major concern which affects both the individual and institution. Knowledge about burnout and associated risk factors which influence the development of burnout is vital for early recognition and intervention. The research question which guided this study was: “What are the factors influencing the degree of burnout experienced by nurses working in neonatal in
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Books on the topic "Analysis of Variance (ANOVA)"

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DeVincenzo, Marie, and Hari Rajagopalan. Analysis of Variance (ANOVA). SAGE Publications, Inc., 2023. http://dx.doi.org/10.4135/9781071910443.

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Rutherford, Andrew, and Andrew Rutherford. ANOVA and ANCOVA: A GLM approach. 2nd ed. Wiley, 2011.

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Rutherford, Andrew. ANOVA and ANCOVA: A GLM approach. 2nd ed. Wiley, 2011.

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Jackson, Sally Ann. Random factors in ANOVA. Sage Publications, 1994.

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S, Fidell Linda, ed. Experimental designs using ANOVA. Thomson/Brooks/Cole, 2007.

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Dario, Basso, ed. Permutation tests for stochastic ordering and ANOVA: Theory and applications with R. Springer, 2009.

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Dario, Basso, ed. Permutation tests for stochastic ordering and ANOVA: Theory and applications with R. Springer, 2009.

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Scott Jones, Julie. Learn to Use Factorial Analysis of Variance (ANOVA) in SPSS With Data From the English Health Survey (Teaching Dataset) (2002). SAGE Publications Ltd., 2019. http://dx.doi.org/10.4135/9781526485786.

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Scott Jones, Julie. Learn to Use Factorial Analysis of Variance (ANOVA) in R With Data From the English Health Survey (Teaching Dataset) (2002). SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526498694.

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Institute of Cost and Management Accountants., ed. Variance analysis. Financial Training, 1986.

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Book chapters on the topic "Analysis of Variance (ANOVA)"

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Quicke, Donald, Buntika A. Butcher, and Rachel Kruft Welton. "Analysis of variance (ANOVA)." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0013a.

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Abstract Analysis of variance is used to analyze the differences between group means in a sample, when the response variable is numeric (real numbers) and the explanatory variable(s) are all categorical. Each explanatory variable may have two or more factor levels, but if there is only one explanatory variable and it has only two factor levels, one should use Student's t-test and the result will be identical. Basically an ANOVA fits an intercept and slopes for one or more of the categorical explanatory variables. ANOVA is usually performed using the linear model function lm, or the more specif
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Quicke, Donald, Buntika A. Butcher, and Rachel Kruft Welton. "Analysis of variance (ANOVA)." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0155.

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Abstract Analysis of variance is used to analyze the differences between group means in a sample, when the response variable is numeric (real numbers) and the explanatory variable(s) are all categorical. Each explanatory variable may have two or more factor levels, but if there is only one explanatory variable and it has only two factor levels, one should use Student's t-test and the result will be identical. Basically an ANOVA fits an intercept and slopes for one or more of the categorical explanatory variables. ANOVA is usually performed using the linear model function lm, or the more specif
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Dugard, Pat, John Todman, and Harry Staines. "Analysis of variance (ANOVA)." In Approaching Multivariate Analysis, 2nd ed. Routledge, 2022. http://dx.doi.org/10.4324/9781003343097-2.

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Acton, Ciaran, Robert Miller, John Maltby, and Deirdre Fullerton. "Analysis of Variance (ANOVA)." In SPSS for Social Scientists. Macmillan Education UK, 2009. http://dx.doi.org/10.1007/978-1-137-01390-3_9.

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Miller, Robert L., Ciaran Acton, Deirdre A. Fullerton, John Maltby, and Jo Campling. "Analysis of Variance (ANOVA)." In SPSS for Social Scientists. Macmillan Education UK, 2002. http://dx.doi.org/10.1007/978-0-230-62968-4_8.

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Lawal, Bayo. "Analysis of Variance (ANOVA)." In Applied Statistical Methods in Agriculture, Health and Life Sciences. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05555-8_6.

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Kaufman, Jörg. "Analysis of Variance (ANOVA)." In Methods and Applications of Statistics in Clinical Trials. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118596333.ch2.

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Goodman, Melody S. "Analysis of variance (ANOVA)." In Biostatistics for Clinical and Public Health Research. Routledge, 2017. http://dx.doi.org/10.4324/9781315155661-16.

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Vasishth, Shravan, and Michael Broe. "Analysis of Variance (ANOVA)." In The Foundations of Statistics: A Simulation-based Approach. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16313-5_5.

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Shahbaba, Babak. "Analysis of Variance (ANOVA)." In Biostatistics with R. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1302-8_9.

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Conference papers on the topic "Analysis of Variance (ANOVA)"

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Bittner, Alvah. "Analysis-of-variance (ANOVA) Assumptions Review: Normality, Variance Equality, and Independence." In XXXIVth Annual International Occupational Ergonomics and Safety Conference. International Society for Occupational Ergonomics and Safety, 2022. http://dx.doi.org/10.47461/isoes.2022_bittner.

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Chan, Jasmine. "Analysis of variance and its applications in Macau educational resarches." In Statistics education for Progress: Youth and Official Statistics. International Association for Statistical Education, 2013. http://dx.doi.org/10.52041/srap.13302.

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In 2012, Macau government approved and passed the “System Framework for Private School Teaching Staff of Non-tertiary Education” in the legislative council. It is aimed at improving non-tertiary teachers’ professionalism in terms of setting hierarchies and provides training continuously. Teachers having a high level of research capacity can improve and solve education issues in Macau. Education Statistics are one of the important methods in research capacity. To develop this idea, therefore, my topic is “Analysis of variance and Its Applications in Macao Educational Researches”.In this paper a
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MUDHOLKAR, GOVIND S., DEO KUMAR SRIVASTAVA, CAROL E. MARCHETTI, and ANIL G. MUDHOLKAR. "TRIMMED ANALYSIS OF VARIANCE: A ROBUST MODIFICATION OF ANOVA." In Proceedings of Statistics 2011 Canada/IMST 2011-FIM XX. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814417983_0012.

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Bokoro, P., and K. Malandala. "Condition assessment of SF6 circuit breakers using analysis of variance (ANOVA)." In 2017 IEEE AFRICON. IEEE, 2017. http://dx.doi.org/10.1109/afrcon.2017.8095682.

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Brusca, S., and R. Lanzafame. "Heat Recovery Steam Generator Optimization Using Analysis of Variance." In ASME 2005 Power Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pwr2005-50008.

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The present work deals with the analysis and optimization of a heat recovery steam generator (HRSG) using the ANalysis Of VAriance (ANOVA). In order to obtain an optimum thermodynamic configuration of a three pressure levels HRSG, a mathematical model of the generator has been implemented using a generic thermodynamic code. Model management and HRSG control logic have been implemented using code’s macros and Microsoft Excel VBA programming languages. The model has been finely tuned and tested using real HRSG running data in the current plant configuration. Using the model, evaporators’ pressur
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Moscalu, Mihaela, Gabriel Dimitriu, Cristina gena Dascalu, and Vasile lucian Boiculese. "ANALYSING THE EFFECT OF THE DEVIATION OF COVARIATES USING MULTIPLE REGRESSION." In eLSE 2018. Carol I National Defence University Publishing House, 2018. http://dx.doi.org/10.12753/2066-026x-18-208.

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Comparing data sets to highlight statistical differences is achieved by applying the t test (two samples) or ANOVA technique (2 or more samples). However, the cause-effect link is not demonstrated using these, even if a statistical significance is obtained. Multiple regression identifies and controls the effect of covariates which can contribute to explaining the observed variation of dependent variable, while reducing the variance error (unexplained variation). For an analysis with known covariates of interest that can affect the dependent variable, an effect adjustment by ANCOVA method is ne
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Zohourkari, Iman, Saeed Assarzadeh, and Mehdi Zohoor. "Modeling and Analysis of Hot Extrusion Metal Forming Process Using Artificial Neural Network and ANOVA." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25333.

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In this paper, a feed-forward back-propagation artificial neural network (BP-ANN) and analysis of variance (ANOVA) are applied to a hot metal extrusion process, establishing a black box model as well as analyzing the effects of relevant process parameters on required forging load, under different operating conditions. Some finite element simulation data on extruding ck-45 steel, adopted from a published research paper, were used to train the neural model employing Levenberg-Marquardt learning algorithm. Die angle (15°–75°), friction coefficient between billet-die material pair (0.4–0.8), punch
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Nasirabadi, Parizad Shojaee, Helene Conseil-Gudla, Sankhya Mohanty, Masoud Jabbari, Rajan Ambat, and Jesper H. Hattel. "Semi-empirical prediction of moisture build-up in an electronic enclosure using analysis of variance (ANOVA)." In 2016 IEEE 18th Electronics Packaging Technology Conference (EPTC). IEEE, 2016. http://dx.doi.org/10.1109/eptc.2016.7861588.

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Karakhan, Ali, John Gambatese, Kasim Alomari, and Ding Liu. "Consideration of Worker Safety in the Design Process: A Statistical-Based Approach Using Analysis of Variance (ANOVA)." In Construction Research Congress 2018. American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784481288.037.

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Danila, Adrian, Delia Ungureanu, Sorin Aurel Moraru, and Nicoleta Voicescu. "An implementation of the variance analysis (ANOVA) for the power factor optimization at distribution level in smart grid." In 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP). IEEE, 2017. http://dx.doi.org/10.1109/optim.2017.7974946.

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Reports on the topic "Analysis of Variance (ANOVA)"

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Watts, Adam. Analysis of Variance of Functional Data (F-ANOVA). Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2282510.

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Becker, Sarah, Heather Sussman, S. Blundell, Vern Vanderbilt, and Igor Semyonov. Analysis of spectropolarimetric responses in the visible and infrared for differentiation between similar materials. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45422.

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Spectropolarimetric research has focused on target detections of materials that have a high degree of contrast from background materials, such as identification of a manmade object embedded in a vegetative background. This study presents an approach using spectropolarimetric imagery in visible, shortwave infrared, and longwave infrared bands to differentiate between similar natural and manmade materials. The method employs Michelson contrast and Kruskal-Wallis one-way analysis of variance (ANOVA) H-test to determine if a distinction can be found in pairwise comparisons of similar and different
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ลือบุญธวัชชัย, พีรพนธ์. การพัฒนารูปแบบจิตบำบัดสัมพันธภาพระหว่างบุคคลสำหรับผู้ป่วยโรคซึมเศร้าในประเทศไทย. จุฬาลงกรณ์มหาวิทยาลัย, 2019. https://doi.org/10.58837/chula.res.2019.14.

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ที่มาและความสำคัญของปัญหา: โรคซึมเศร้าเป็นโรคทางจิตเวชที่พบบ่อย ส่งผลกระทบต่อความสูญเสียทางเศรษฐกิจและสังคม จิตบำบัดสัมพันธภาพระหว่างบุคคลเป็นจิตบำบัดรูปแบบหนึ่งที่มีประสิทธิภาพในการรักษาโรคซึมเศร้า การนำมาปรับใช้ในประเทศไทย ต้องคำนึงถึงบริบทด้านสังคมวัฒนธรรมร่วมด้วย จึงมีความจำเป็นในการนำมาปรับพัฒนาให้เหมาะสมกับบริบทของประเทศไทย ผู้วิจัยได้พัฒนาและปรับรูปแบบการบำบัดเป็นรูปแบบกลุ่ม และศึกษาประสิทธิภาพในการรักษาอาการซึมเศร้าในผู้ป่วยโรคซึมเศร้าในประเทศไทย วัตถุประสงค์ของการวิจัย: เพื่อศึกษาประสิทธิภาพของจิตบำบัดสัมพันธภาพระหว่างบุคคลรูปแบบกลุ่มในการลดอาการซึมเศร้าของผู้ป่วยโรคซึมเศร้า โดยเปรียบ
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Dzhangarov, A. I. Multivariate analysis of variance analysis software. Engineering Herald of Don, 2019. http://dx.doi.org/10.18411/0236-8898-1123.

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Dzhangarov, A. I. Multivariate analysis of variance analysis software. Engineering Herald of Don, 2019. http://dx.doi.org/10.18411/0236-8898-1123-2020.

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Kim, Joseph J., Samuel Dominguez, and Luis Diaz. Freight Demand Model for Southern California Freeways with Owner–Operator Truck Drivers. Mineta Transportation Institute, 2020. http://dx.doi.org/10.31979/mti.2020.1931.

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This study evaluates the demand for truck-only toll lanes on Southern California freeways with owner–operator truck drivers. The study implemented the stated preference survey method to estimate the value placed by drivers on time, reliability, and safety measures using various scenarios geared towards assessing those values. The project team met face-to-face with owner- operator truck drivers near the Ports of Los Angeles and Long Beach to understand the drivers’ perspectives regarding truck-only toll lanes on Southern California freeways. A data set containing 31 survey responses is obtained
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Goodall, Colin. The Analysis of Averages and the Analysis of Variance. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada198467.

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Taylor, K. E., and C. Covey. Analysis of Variance Including the Diurnal Cycle. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1460516.

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Verrill, Steve, and David E. Kretschmann. Reminder about potentially serious problems with a type of blocked ANOVA analysis. U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, 2017. http://dx.doi.org/10.2737/fpl-rp-683.

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Poyer, D. A. Residential energy consumption: An analysis-of-variance study. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/5757461.

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